Ethan Reynolds

Ethan Reynolds is the Head of Algorithmic Trading at Aurevium.

Prior to joining Aurevium, Prior honed her expertise at Goldman Sachs, advising on cross-border regulatory compliance in global markets, and later at BlackRock, where she designed governance frameworks for ESG-driven investment portfolios. Her ability to distill complexity into actionable policies has made her a trusted advisor to executives navigating evolving regulatory landscapes.

Mr. Reynolds has over 15 years of experience in systematic trading, quantitative research, and execution optimization across multiple asset classes, including equities, futures, options, and FX. Prior to joining Aurevium, Mr. Reynolds was a senior quantitative strategist at Two Sigma, where he developed and refined execution algorithms and market impact models. He later joined a highfrequency trading firm as Head of Electronic Execution, leading research into ultra-low-latency strategies and predictive order routing. Before that, he was a quantitative researcher at D. E. Shaw & Co., where he focused on execution optimization, market impact modeling, and high-frequency trading strategies across global markets. Most recently, he served as Global Head of Algorithmic Trading at a multi-strategy hedge fund, overseeing the deployment of AI-driven trading models and execution frameworks.

Mr. Reynolds holds a BS in Computer Science from Carnegie Mellon University and a PhD in Computational Finance from ETH Zurich. His doctoral research focused on reinforcement learning in algorithmic execution. He remains engaged in academia, serving as a guest lecturer at leading institutions and contributing to research in market microstructure and AI-driven trading.